Improved Differential Evolution for Enhancing the Aggregated Channel Estimation of RIS-Aided Cell-Free Massive MIMO

Cell-free massive MIMO; differential evolution; reconfigurable intelligent surface; Cell-free; Cell-free massive multiple-input multiple-output; Differential Evolution; Improved differential evolutions; Multiple inputs; Multiple outputs; Multiple-Input Multiple- Output systems; Reconfigurable; Reconfigurable intelligent surface; Surface phasis; Automotive Engineering; Aerospace Engineering; Computer Networks and Communications; Electrical and Electronic Engineering

Abstract :

[en] Cell-Free Massive multiple-input multiple-output (MIMO) systems are investigated with the support of a reconfigurable intelligent surface (RIS). The RIS phase shifts are designed for improved channel estimation in the presence of spatial correlation. Specifically, we formulate the channel estimate and estimation error expressions using linear minimum mean square error (LMMSE) estimation for the aggregated channels. An optimization problem is then formulated to minimize the average normalized mean square error (NMSE) subject to practical phase shift constraints. To circumvent the problem of inherent nonconvexity, we then conceive an enhanced version of the differential evolution algorithm that is capable of avoiding local minima by introducing an augmentation operator applied to some high-performing Diffential Evolution (DE) individuals. Numerical results indicate that our proposed algorithm can significantly improve the channel estimation quality of the state-of-the-art benchmarks.

Disciplines :

Computer science

Author, co-author :

Chien, Trinh Van ; Hanoi University of Science and Technology, School of Information and Communications Technology, Hanoi, Viet Nam

Viet, Nguyen Hoang ; Hanoi University of Science and Technology, School of Information and Communications Technology, Hanoi, Viet Nam

CHATZINOTAS, Symeon ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom

Hanzo, Lajos ; University of Southampton, Department of Electronics and Computer Science, Southampton, United Kingdom

External co-authors :

yes

Language :

English

Title :

Improved Differential Evolution for Enhancing the Aggregated Channel Estimation of RIS-Aided Cell-Free Massive MIMO

Publication date :

15 July 2025

Journal title :

IEEE Transactions on Vehicular Technology

ISSN :

0018-9545

Publisher :

Institute of Electrical and Electronics Engineers Inc.

Pages :

1-6

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

http://xplorestaging.ieee.org/ielx8/25/4356907/11080325.pdf?arnumber=11080325

Available on ORBilu :

since 14 November 2025

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